{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/gakco-a-fast-gapped-k-mer-string-kernel-using","title":"GaKCo: a Fast GApped k-mer string Kernel using COunting","arxiv_id":"1704.07468","date":"2017-04-24","proceeding":null,"authors":["Ritambhara Singh","Arshdeep Sekhon","Kamran Kowsari","Jack Lanchantin","Beilun Wang","Yanjun Qi"],"abstract":"String Kernel (SK) techniques, especially those using gapped $k$-mers as\nfeatures (gk), have obtained great success in classifying sequences like DNA,\nprotein, and text. However, the state-of-the-art gk-SK runs extremely slow when\nwe increase the dictionary size ($\\Sigma$) or allow more mismatches ($M$). This\nis because current gk-SK uses a trie-based algorithm to calculate co-occurrence\nof mismatched substrings resulting in a time cost proportional to\n$O(\\Sigma^{M})$. We propose a \\textbf{fast} algorithm for calculating\n\\underline{Ga}pped $k$-mer \\underline{K}ernel using \\underline{Co}unting\n(GaKCo). GaKCo uses associative arrays to calculate the co-occurrence of\nsubstrings using cumulative counting. This algorithm is fast, scalable to\nlarger $\\Sigma$ and $M$, and naturally parallelizable. We provide a rigorous\nasymptotic analysis that compares GaKCo with the state-of-the-art gk-SK.\nTheoretically, the time cost of GaKCo is independent of the $\\Sigma^{M}$ term\nthat slows down the trie-based approach. Experimentally, we observe that GaKCo\nachieves the same accuracy as the state-of-the-art and outperforms its speed by\nfactors of 2, 100, and 4, on classifying sequences of DNA (5 datasets), protein\n(12 datasets), and character-based English text (2 datasets), respectively.\n  GaKCo is shared as an open source tool at\n\\url{https://github.com/QData/GaKCo-SVM}","url_abs":"http://arxiv.org/abs/1704.07468v3","url_pdf":"http://arxiv.org/pdf/1704.07468v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"gakco-a-fast-gapped-k-mer-string-kernel-using","repo_url":"https://github.com/QData/GaKCo-SVM","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[],"methods":[{"method_slug":"speed","method_name":"SPEED"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}